SQL Server Basics and Fundamentals


Introduction to SQL:  
SQL is a standard language for accessing and manipulating databases.  

What is SQL and TSQL?

  • SQL stands for Structured Query Language and TSQL is referred as Transact SQL.
  • SQL lets you access and manipulate databases to retrieve data and the information required.
  • SQL is an ANSI (American National Standards Institute) standard.

What Can SQL do?

  • SQL can execute queries against a database
  • SQL can retrieve data from a database
  • SQL can insert records in a database
  • SQL can update records in a database
  • SQL can delete records from a database
  • SQL can create new databases
  • SQL can create new tables in a database
  • SQL can create stored procedures in a database
  • SQL can create views in a database
  • SQL can set permissions on tables, procedures, and views
  • SQL can be used to check the processes running
  • SQL can be used in tuning the processes
  • SQL can be used to restrict users and more….

SQL is a Standard – BUT….

Although SQL is an ANSI (American National Standards Institute) standard, there are many different versions of the SQL language.  
However, to be compliant with the ANSI standard, they all support at least the major commands (such as SELECT, UPDATE, DELETE, INSERT, WHERE) in a similar manner.  
Note: Most of the SQL database programs also have their own proprietary extensions in addition to the SQL standard!  


Using SQL in Your Web Site

To build a web site that shows some data from a database, you will need the following:  

  • An RDBMS database program (i.e. MS Access, SQL Server, MySQL)
  • A server-side scripting language, like PHP or ASP
  • SQL
  • HTML / CSS

RDBMS

RDBMS stands for Relational Database Management System.  
RDBMS is the basis for SQL, and for all modern database systems like MS SQL Server, IBM DB2, Oracle, MySQL, and Microsoft Access.  
The data in RDBMS is stored in database objects called tables.  
A table is a collections of related data entries and it consists of columns and rows.  

SQL Server DDL and DML commands

SQL can be divided into two parts: The  Data Definition Language (DDL) and Data Manipulation Language (DML)  
The query and update commands form the DML part of SQL:  

  • SELECT – extracts data from a database
  • UPDATE – updates data in a database
  • DELETE – deletes data from a database
  • INSERT INTO – inserts new data into a database

The DDL part of SQL permits database tables to be created or deleted. It also define indexes (keys), specify links between tables, and impose constraints between tables. The most important DDL statements in SQL are:  

  • CREATE DATABASE – creates a new database
  • ALTER DATABASE – modifies a database
  • CREATE TABLE – creates a new table
  • ALTER TABLE – modifies a table
  • DROP TABLE – deletes a table
  • CREATE INDEX – creates an index (search key)
  • DROP INDEX – deletes an index

   


 

The SQL SELECT Statement

   
The SELECT statement is used to select data from a database or to retrieve information.  
The result is stored in a result table, called the result-set.  

SQL SELECT Syntax

SELECT column_name(s)
FROM table_name

and 

SELECT * FROM table_name

Note: SQL is not case sensitive. SELECT is the same as select.  

Example for SELECT Statement

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Now we want to select the content of the columns named “LastName” and “FirstName” from the table above.  
We use the following SELECT statement: 

SELECT LastName,FirstName FROM Persons

The result-set will look like this: 

LastName FirstName
Hansen Ola
Svendson Tove
Pettersen Kari

  


SELECT * Example

Now we want to select all the columns from the “Persons” table.  
We use the following SELECT statement:  

SELECT * FROM Persons

Tip: The asterisk (*) is a quick way of selecting all columns!  
The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

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SQL WHERE Clause and its usage:  
The WHERE clause is used to filter records.  


The WHERE clause is used to extract only those records that fulfill a specified criterion.  

SQL syntax for WHERE clause

SELECT column_name(s)
FROM table_name
WHERE column_name operator value

  


Simple WHERE Clause statement example

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Now we want to select only the persons living in the city “Sandnes” from the table above.  
We use the following SELECT statement: 

SELECT * FROM Persons
WHERE City=’Sandnes’

The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes

Operators Allowed in the WHERE Clause

With the WHERE clause, the following operators can be used: 

Operator Description
= Equal
<> Not equal
> Greater than
< Less than
>= Greater than or equal
<= Less than or equal
BETWEEN Between an inclusive range
LIKE Search for a pattern
IN If you know the exact value you want to return for at least one of the columns

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SQL ORDER BY CLAUSE  
The ORDER BY keyword is used to sort the result-set.  


ORDER BY key word in SQL

The ORDER BY keyword is used to sort the result-set by a specified column.  
The ORDER BY keyword sort the records in ascending order by default.  
If you want to sort the records in a descending order, you can use the DESC keyword.  

SQL ORDER BY Syntax

SELECT column_name(s)
FROM table_name
ORDER BY column_name(s) ASC|DESC

  


Syntax for ORDER BY

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Tom Vingvn 23 Stavanger

Now we want to select all the persons from the table above, however, we want to sort the persons by their last name.  
We use the following SELECT statement: 

SELECT * FROM Persons
ORDER BY LastName

The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
4 Nilsen Tom Vingvn 23 Stavanger
3 Pettersen Kari Storgt 20 Stavanger
2 Svendson Tove Borgvn 23 Sandnes

  


Syntax using – ORDER BY DESC

Now we want to select all the persons from the table above, however, we want to sort the persons descending by their last name.  
We use the following SELECT statement: 

SELECT * FROM Persons
ORDER BY LastName DESC

The result-set will look like this: 

P_Id LastName FirstName Address City
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Tom Vingvn 23 Stavanger
1 Hansen Ola Timoteivn 10 Sandnes

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INSERT INTO syntax in SQL  
The INSERT INTO statement is used to insert new records in a table.  


The INSERT INTO statement is used to insert a new row in a table.  

Syntax : INSERT INTO

It is possible to write the INSERT INTO statement in two forms.  
The first form doesn’t specify the column names where the data will be inserted, only their values: 

INSERT INTO table_name
VALUES (value1, value2, value3,…)

The second form specifies both the column names and the values to be inserted: 

INSERT INTO table_name (column1, column2, column3,…)
VALUES (value1, value2, value3,…)

SQL INSERT INTO Example

We have the following “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Now we want to insert a new row in the “Persons” table.  
We use the following SQL statement: 

INSERT INTO Persons
VALUES (4,’Nilsen’, ‘Johan’, ‘Bakken 2’, ‘Stavanger’)

The “Persons” table will now look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Johan Bakken 2 Stavanger

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UPDATE Syntax in SQL   
The UPDATE statement is used to update records in a table.  


The UPDATE statement is used to update existing records in a table.  

SQL UPDATE Syntax

UPDATE table_name
SET column1=value, column2=value2,…
WHERE some_column=some_value

Note: Notice the WHERE clause in the UPDATE syntax. The WHERE clause specifies which record or records that should be updated. If you omit the WHERE clause, all records will be updated!  


UPDATE syntax and example

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Johan Bakken 2 Stavanger
5 Tjessem Jakob    

Now we want to update the person “Tjessem, Jakob” in the “Persons” table.  
We use the following SQL statement: 

UPDATE Persons
SET Address=’Nissestien 67′, City=’Sandnes’
WHERE LastName=’Tjessem’ AND FirstName=’Jakob’

The “Persons” table will now look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Johan Bakken 2 Stavanger
5 Tjessem Jakob Nissestien 67 Sandnes

  


 UPDATE  Syntax Warning  

Be careful when updating records. If we had omitted the WHERE clause in the example above, like this: 

UPDATE Persons
SET Address=’Nissestien 67′, City=’Sandnes’

The “Persons” table would have looked like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Nissestien 67 Sandnes
2 Svendson Tove Nissestien 67 Sandnes
3 Pettersen Kari Nissestien 67 Sandnes
4 Nilsen Johan Nissestien 67 Sandnes
5 Tjessem Jakob Nissestien 67 Sandnes

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DELETE Statement in SQL  
“IMPORTANT”  
The DELETE statement is used to delete records in a table.  


The DELETE statement is used to delete rows in a table.  

SQL DELETE Syntax

DELETE FROM table_name
WHERE some_column=some_value

Note: Notice the WHERE clause in the DELETE syntax. The WHERE clause specifies which record or records that should be deleted. If you omit the WHERE clause, all records will be deleted!  


SQL syntax for DELETE and example

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Johan Bakken 2 Stavanger
5 Tjessem Jakob Nissestien 67 Sandnes

Now we want to delete the person “Tjessem, Jakob” in the “Persons” table.  
We use the following SQL statement: 

DELETE FROM Persons
WHERE LastName=’Tjessem’ AND FirstName=’Jakob’

The “Persons” table will now look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Johan Bakken 2 Stavanger

  


Delete All Rows from a TABLE  

It is possible to delete all rows in a table without deleting the table. This means that the table structure, attributes, and indexes will be intact: 

DELETE FROM table_nameorDELETE * FROM table_name 
  

Note: Be very careful when deleting records. You cannot undo this statement.  
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SQL TOP and syntax, how to use TOP in SQL:  
The TOP clause is used to specify the number of records to return.  
The TOP clause can be very useful on large tables with thousands of records. Returning a large number of records can impact on performance.  
Note: Not all database systems support the TOP clause.  

SQL Server Syntax

SELECT TOP number|percent column_name(s)
FROM table_name

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Tom Vingvn 23 Stavanger

Now we want to select only the two first records in the table above.  
We use the following SELECT statement: 

SELECT TOP 2 * FROM Persons

The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes

  


SQL TOP PERCENT Example

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger
4 Nilsen Tom Vingvn 23 Stavanger

Now we want to select only 50% of the records in the table above.  
We use the following SELECT statement: 

SELECT TOP 50 PERCENT * FROM Persons

The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes

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OPERATOR  
SQL Server LIKE operator  
The LIKE operator is used in a WHERE clause to search for a specified pattern in a column.  


LIKE

The LIKE operator is used to search for a specified pattern in a column.  

SQL LIKE Syntax

SELECT column_name(s)
FROM table_name
WHERE column_name LIKE pattern

  


Syntax and example for LIKE

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Now we want to select the persons living in a city that starts with “s” from the table above.  
We use the following SELECT statement: 

SELECT * FROM Persons
WHERE City LIKE ‘s%’

The “%” sign can be used to define wildcards (missing letters in the pattern) both before and after the pattern.  
The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Next, we want to select the persons living in a city that ends with an “s” from the “Persons” table.  
We use the following SELECT statement: 

SELECT * FROM Persons
WHERE City LIKE ‘%s’

The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes

Next, we want to select the persons living in a city that contains the pattern “tav” from the “Persons” table.  
We use the following SELECT statement: 

SELECT * FROM Persons
WHERE City LIKE ‘%tav%’

The result-set will look like this: 

P_Id LastName FirstName Address City
3 Pettersen Kari Storgt 20 Stavanger

It is also possible to select the persons living in a city that NOT contains the pattern “tav” from the “Persons” table, by using the NOT keyword.  
We use the following SELECT statement: 

SELECT * FROM Persons
WHERE City NOT LIKE ‘%tav%’

The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes

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OPERATOR  
“IN”  
The IN operator allows you to specify multiple values in a WHERE clause.  

SQL IN Syntax

SELECT column_name(s)
FROM table_name
WHERE column_name IN (value1,value2,…)

  


“IN”

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Now we want to select the persons with a last name equal to “Hansen” or “Pettersen” from the table above.  
We use the following SELECT statement: 

SELECT * FROM Persons
WHERE LastName IN (‘Hansen’,’Pettersen’)

The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

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OPERATOR   
“BETWEEN”  
The BETWEEN operator is used in a WHERE clause to select a range of data between two values.  


The BETWEEN Operator

The BETWEEN operator selects a range of data between two values. The values can be numbers, text, or dates.  

SQL BETWEEN Syntax

SELECT column_name(s)
FROM table_name
WHERE column_name
BETWEEN value1 AND value2

  


BETWEEN Operator

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Now we want to select the persons with a last name alphabetically between “Hansen” and “Pettersen” from the table above.  
We use the following SELECT statement: 

SELECT * FROM Persons
WHERE LastName
BETWEEN ‘Hansen’ AND ‘Pettersen’

The result-set will look like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes

Note: The BETWEEN operator is treated differently in different databases.  
In some databases, persons with the LastName of “Hansen” or “Pettersen” will not be listed, because the BETWEEN operator only selects fields that are between and excluding the test values).  
In other databases, persons with the LastName of “Hansen” or “Pettersen” will be listed, because the BETWEEN operator selects fields that are between and including the test values).  
And in other databases, persons with the LastName of “Hansen” will be listed, but “Pettersen” will not be listed (like the example above), because the BETWEEN operator selects fields between the test values, including the first test value and excluding the last test value.  
Therefore: Check how your database treats the BETWEEN operator.  


To display the persons outside the range in the previous example, use NOT BETWEEN: 

SELECT * FROM Persons
WHERE LastName
NOT BETWEEN ‘Hansen’ AND ‘Pettersen’

The result-set will look like this: 

P_Id LastName FirstName Address City
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

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“JOINS”  
SQL SERVER “JOINS” and syntax  
SQL joins are used to query data from two or more tables, based on a relationship between certain columns in these tables.  


SQL JOIN

The JOIN keyword is used in an SQL statement to query data from two or more tables, based on a relationship between certain columns in these tables.  
Tables in a database are often related to each other with keys.  
A primary key is a column (or a combination of columns) with a unique value for each row. Each primary key value must be unique within the table. The purpose is to bind data together, across tables, without repeating all of the data in every table.  
Look at the “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Note that the “P_Id” column is the primary key in the “Persons” table. This means that no two rows can have the same P_Id. The P_Id distinguishes two persons even if they have the same name.  
Next, we have the “Orders” table: 

O_Id OrderNo P_Id
1 77895 3
2 44678 3
3 22456 1
4 24562 1
5 34764 15

Note that the “O_Id” column is the primary key in the “Orders” table and that the “P_Id” column refers to the persons in the “Persons” table without using their names.  
Notice that the relationship between the two tables above is the “P_Id” column.  


Types of SQL JOINs

Before we continue with examples, we will list the types of JOIN you can use, and the differences between them.  

  • JOIN: Return rows when there is at least one match in both tables
  • LEFT JOIN: Return all rows from the left table, even if there are no matches in the right table
  • RIGHT JOIN: Return all rows from the right table, even if there are no matches in the left table
  • FULL JOIN: Return rows when there is a match in one of the tables

   
SQL Server INNER JOIN syntax and example  
The INNER JOIN keyword return rows when there is at least one match in both tables.  

SQL INNER JOIN Syntax

SELECT column_name(s)
FROM table_name1
INNER JOIN table_name2
ON table_name1.column_name=table_name2.column_name

PS: INNER JOIN is the same as JOIN.  


INNER JOIN syntax

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

The “Orders” table: 

O_Id OrderNo P_Id
1 77895 3
2 44678 3
3 22456 1
4 24562 1
5 34764 15

Now we want to list all the persons with any orders.  
We use the following SELECT statement: 

SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
INNER JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName

The result-set will look like this: 

LastName FirstName OrderNo
Hansen Ola 22456
Hansen Ola 24562
Pettersen Kari 77895
Pettersen Kari 44678

The INNER JOIN keyword return rows when there is at least one match in both tables. If there are rows in “Persons” that do not have matches in “Orders”, those rows will NOT be listed.  
SQL Server “LEFT JOIN” Syntax  
The LEFT JOIN keyword returns all rows from the left table (table_name1), even if there are no matches in the right table (table_name2).  

SQL LEFT JOIN Syntax

SELECT column_name(s)
FROM table_name1
LEFT JOIN table_name2
ON table_name1.column_name=table_name2.column_name

PS: In some databases LEFT JOIN is called LEFT OUTER JOIN.  


LEFT JOIN

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

The “Orders” table: 

O_Id OrderNo P_Id
1 77895 3
2 44678 3
3 22456 1
4 24562 1
5 34764 15

Now we want to list all the persons and their orders – if any, from the tables above.  
We use the following SELECT statement: 

SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
LEFT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName

The result-set will look like this: 

LastName FirstName OrderNo
Hansen Ola 22456
Hansen Ola 24562
Pettersen Kari 77895
Pettersen Kari 44678
Svendson Tove  

The LEFT JOIN keyword returns all the rows from the left table (Persons), even if there are no matches in the right table (Orders).  
SQL Server “RIGHT JOIN” syntax and example  
The RIGHT JOIN keyword Return all rows from the right table (table_name2), even if there are no matches in the left table (table_name1).  

SQL RIGHT JOIN Syntax

SELECT column_name(s)
FROM table_name1
RIGHT JOIN table_name2
ON table_name1.column_name=table_name2.column_name

PS: In some databases RIGHT JOIN is called RIGHT OUTER JOIN.  


RIGHT JOIN

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

The “Orders” table: 

O_Id OrderNo P_Id
1 77895 3
2 44678 3
3 22456 1
4 24562 1
5 34764 15

Now we want to list all the orders with containing persons – if any, from the tables above.  
We use the following SELECT statement: 

SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
RIGHT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName

The result-set will look like this: 

LastName FirstName OrderNo
Hansen Ola 22456
Hansen Ola 24562
Pettersen Kari 77895
Pettersen Kari 44678
    34764

The RIGHT JOIN keyword returns all the rows from the right table (Orders), even if there are no matches in the left table (Persons).  
    
SQL Server “FULL JOIN” Syntax and example  
The FULL JOIN keyword return rows when there is a match in one of the tables. 

SELECT column_name(s)
FROM table_name1
FULL JOIN table_name2
ON table_name1.column_name=table_name2.column_name

  


FULL JOIN

The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

The “Orders” table: 

O_Id OrderNo P_Id
1 77895 3
2 44678 3
3 22456 1
4 24562 1
5 34764 15

Now we want to list all the persons and their orders, and all the orders with their persons.  
We use the following SELECT statement: 

SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
FULL JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName

The result-set will look like this: 

LastName FirstName OrderNo
Hansen Ola 22456
Hansen Ola 24562
Pettersen Kari 77895
Pettersen Kari 44678
Svendson Tove  
    34764

The FULL JOIN keyword returns all the rows from the left table (Persons), and all the rows from the right table (Orders). If there are rows in “Persons” that do not have matches in “Orders”, or if there are rows in “Orders” that do not have matches in “Persons”, those rows will be listed as well.  
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“UNION”  
SQL Server UNION  
The  SQL UNION operator combines two or more SELECT statements.  


The UNION operator is used to combine the result-set of two or more SELECT statements.  

Notice that each SELECT statement within the UNION must have the same number of columns. The columns must also have similar data types. Also, the columns in each SELECT statement must be in the same order.  

SQL UNION Syntax

SELECT column_name(s) FROM table_name1
UNION
SELECT column_name(s) FROM table_name2

Note: The UNION operator selects only distinct values by default. To allow duplicate values, use UNION ALL.  

SQL UNION ALL Syntax

SELECT column_name(s) FROM table_name1
UNION ALL
SELECT column_name(s) FROM table_name2

PS: The column names in the result-set of a UNION are always equal to the column names in the first SELECT statement in the UNION.  


“UNION”

Look at the following tables:  
“Employees_Norway”

E_ID E_Name
01 Hansen, Ola
02 Svendson, Tove
03 Svendson, Stephen
04 Pettersen, Kari

“Employees_USA”

E_ID E_Name
01 Turner, Sally
02 Kent, Clark
03 Svendson, Stephen
04 Scott, Stephen

Now we want to list all the different employees in Norway and USA.  
We use the following SELECT statement: 

SELECT E_Name FROM Employees_Norway
UNION
SELECT E_Name FROM Employees_USA

The result-set will look like this: 

E_Name
Hansen, Ola
Svendson, Tove
Svendson, Stephen
Pettersen, Kari
Turner, Sally
Kent, Clark
Scott, Stephen

Note: This command cannot be used to list all employees in Norway and USA. In the example above we have two employees with equal names, and only one of them will be listed. The UNION command selects only distinct values.  


 “UNION ALL”

Now we want to list all employees in Norway and USA: 

SELECT E_Name FROM Employees_Norway
UNION ALL
SELECT E_Name FROM Employees_USA

Result 

E_Name
Hansen, Ola
Svendson, Tove
Svendson, Stephen
Pettersen, Kari
Turner, Sally
Kent, Clark
Svendson, Stephen
Scott, Stephen

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SQL Server “SELECT INTO” syntax and example  
The SQL SELECT INTO statement can be used to create backup copies of tables.  


The SELECT INTO statement selects data from one table and inserts it into a different table.  

The SELECT INTO statement is most often used to create backup copies of tables.  

SQL SELECT INTO Syntax

We can select all columns into the new table: 

SELECT *
INTO new_table_name [IN externaldatabase]
FROM old_tablename

Or we can select only the columns we want into the new table: 

SELECT column_name(s)
INTO new_table_name [IN externaldatabase]
FROM old_tablename

  


Make a Backup Copy – Now we want to make an exact copy of the data in our “Persons” table.  

We use the following SQL statement: 

SELECT *
INTO Persons_Backup
FROM Persons

We can also use the IN clause to copy the table into another database: 

SELECT *
INTO Persons_Backup IN ‘Backup.mdb’
FROM Persons

We can also copy only a few fields into the new table: 

SELECT LastName,FirstName
INTO Persons_Backup
FROM Persons

  


“SELECT INTO” – With a WHERE Clause

We can also add a WHERE clause.  
The following SQL statement creates a “Persons_Backup” table with only the persons who lives in the city “Sandnes”: 

SELECT LastName,Firstname
INTO Persons_Backup
FROM Persons
WHERE City=’Sandnes’

  


“SELECT INTO” – Joined Tables

Selecting data from more than one table is also possible.  
The following example creates a “Persons_Order_Backup” table contains data from the two tables “Persons” and “Orders”: 

SELECT Persons.LastName,Orders.OrderNo
INTO Persons_Order_Backup
FROM Persons
INNER JOIN Orders
ON Persons.P_Id=Orders.P_Id
 __________________________________________________________________________________________ “CREATE”  
SQL CREATE Syntax and example  
The CREATE DATABASE statement is used to create a database.  

“CREATE DATABASE” Syntax

CREATE DATABASE database_name

CREATE DATABASE ExampleNow we want to create a database called “my_db”. We use the following CREATE DATABASE statement:

CREATE DATABASE PRODUCTION

Database tables can be added with the CREATE TABLE statement.  

“CREATE TABLE” Syntax and example  
The CREATE TABLE statement is used to create a table in a database.  

SQL CREATE TABLE Syntax

CREATE TABLE table_name
(
column_name1 data_type,
column_name2 data_type,
column_name3 data_type,
….
)

The data type specifies what type of data the column can hold.  Learn SQL Server DATATYPES in BOL  


Now we want to create a table called “Persons” that contains five columns: P_Id, LastName, FirstName, Address, and City.  
We use the following CREATE TABLE statement: 

CREATE TABLE Persons
(
P_Id int,
LastName varchar(255),
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)

The P_Id column is of type int and will hold a number. The LastName, FirstName, Address, and City columns are of type varchar with a maximum length of 255 characters.  
The empty “Persons” table will now look like this: 

P_Id LastName FirstName Address City
         

__________________________________________________________________________________________ 
“CONSTRAINTS”  

SQL Constraints

Constraints are used to limit the type of data that can go into a table.  
Constraints can be specified when a table is created (with the CREATE TABLE statement) or after the table is created (with the ALTER TABLE statement).  
We will focus on the following constraints:  

  • NOT NULL
  • UNIQUE
  • PRIMARY KEY
  • FOREIGN KEY
  • CHECK
  • DEFAULT

SQL PRIMARY KEY Constraint

The PRIMARY KEY constraint uniquely identifies each record in a database table.  
Primary keys must contain unique values.  
A primary key column cannot contain NULL values.  
Each table should have a primary key, and each table can have only ONE primary key.  


SQL PRIMARY KEY Constraint on CREATE TABLE

The following SQL creates a PRIMARY KEY on the “P_Id” column when the “Persons” table is created: 

CREATE TABLE Persons
(
P_Id int NOT NULL PRIMARY KEY,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)

To allow naming of a PRIMARY KEY constraint, and for defining a PRIMARY KEY constraint on multiple columns, use the following SQL syntax: 

CREATE TABLE Persons
(
P_Id int NOT NULL,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255),
CONSTRAINT pk_PersonID PRIMARY KEY (P_Id,LastName)
)

  


SQL PRIMARY KEY Constraint on ALTER TABLE

To create a PRIMARY KEY constraint on the “P_Id” column when the table is already created, use the following SQL: 

ALTER TABLE Persons
ADD PRIMARY KEY (P_Id)

To allow naming of a PRIMARY KEY constraint, and for defining a PRIMARY KEY constraint on multiple columns, use the following SQL syntax: 

ALTER TABLE Persons
ADD CONSTRAINT pk_PersonID PRIMARY KEY (P_Id,LastName)

Note: If you use the ALTER TABLE statement to add a primary key, the primary key column(s) must already have been declared to not contain NULL values (when the table was first created).  


To DROP a PRIMARY KEY Constraint

To drop a PRIMARY KEY constraint, use the following SQL:  
SQL Server  

ALTER TABLE Persons
DROP CONSTRAINT pk_PersonID 

SQL FOREIGN KEY Constraint

A FOREIGN KEY in one table points to a PRIMARY KEY in another table.  
Let’s illustrate the foreign key with an example. Look at the following two tables:  
The “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

The “Orders” table: 

O_Id OrderNo P_Id
1 77895 3
2 44678 3
3 22456 2
4 24562 1

Note that the “P_Id” column in the “Orders” table points to the “P_Id” column in the “Persons” table.  
The “P_Id” column in the “Persons” table is the PRIMARY KEY in the “Persons” table.  
The “P_Id” column in the “Orders” table is a FOREIGN KEY in the “Orders” table.  
The FOREIGN KEY constraint is used to prevent actions that would destroy links between tables.  
The FOREIGN KEY constraint also prevents that invalid data form being inserted into the foreign key column, because it has to be one of the values contained in the table it points to.  

 

 

 


SQL FOREIGN KEY Constraint on CREATE TABLE

The following SQL creates a FOREIGN KEY on the “P_Id” column when the “Orders” table is created:  

 
CREATE TABLE Orders
(
O_Id int NOT NULL PRIMARY KEY,
OrderNo int NOT NULL,
P_Id int FOREIGN KEY REFERENCES Persons(P_Id)
)

To allow naming of a FOREIGN KEY constraint, and for defining a FOREIGN KEY constraint on multiple columns, use the following SQL syntax:  

CREATE TABLE Orders
(
O_Id int NOT NULL,
OrderNo int NOT NULL,
P_Id int,
PRIMARY KEY (O_Id),
CONSTRAINT fk_PerOrders FOREIGN KEY (P_Id)
REFERENCES Persons(P_Id)
)
 

 

 


SQL FOREIGN KEY Constraint on ALTER TABLE

To create a FOREIGN KEY constraint on the “P_Id” column when the “Orders” table is already created, use the following SQL: 

 

To allow naming of a FOREIGN KEY constraint, and for defining a FOREIGN KEY constraint on multiple columns, use the following SQL syntax: 

ALTER TABLE Orders
ADD CONSTRAINT fk_PerOrders
FOREIGN KEY (P_Id)
REFERENCES Persons(P_Id)

To DROP a FOREIGN KEY Constraint

To drop a FOREIGN KEY constraint, use the following SQL: 

ALTER TABLE Orders
DROP CONSTRAINT fk_PerOrders

_________________________________________________________________________________________ 
  
CREATE INDEXES 
The CREATE INDEX statement is used to create indexes in tables. 
Indexes allow the database application to find data fast; without reading the whole table. 


Indexes

An index can be created in a table to find data more quickly and efficiently. 
The users cannot see the indexes, they are just used to speed up searches/queries. 
Note: Updating a table with indexes takes more time than updating a table without (because the indexes also need an update). So you should only create indexes on columns (and tables) that will be frequently searched against. 

SQL CREATE INDEX Syntax

Creates an index on a table. Duplicate values are allowed: 

CREATE INDEX index_name
ON table_name (column_name)

SQL CREATE UNIQUE INDEX Syntax

Creates a unique index on a table. Duplicate values are not allowed: 

CREATE UNIQUE INDEX index_name
ON table_name (column_name)

Note: The syntax for creating indexes varies amongst different databases. Therefore: Check the syntax for creating indexes in your database. 


“CREATE INDEX” 
The SQL statement below creates an index named “PIndex” on the “LastName” column in the “Persons” table: 

CREATE INDEX PIndex
ON Persons (LastName)

If you want to create an index on a combination of columns, you can list the column names within the parentheses, separated by commas: 

CREATE INDEX PIndex
ON Persons (LastName, FirstName)
 
______________________________________________________________________________________ 
   
Indexes, tables, and databases can easily be deleted/removed with the DROP statement. 


The DROP INDEX Statement

The DROP INDEX statement is used to delete an index in a table. 

DROP INDEX Syntax for MS Access:

DROP INDEX index_name ON table_name

DROP INDEX Syntax for MS SQL Server:

DROP INDEX table_name.index_name

DROP INDEX Syntax for DB2/Oracle:

DROP INDEX index_name

DROP INDEX Syntax for MySQL:

ALTER TABLE table_name DROP INDEX index_name

The DROP TABLE Statement

The DROP TABLE statement is used to delete a table. 

DROP TABLE table_name

The DROP DATABASE Statement

The DROP DATABASE statement is used to delete a database. 

DROP DATABASE database_name

The TRUNCATE TABLE Statement

What if we only want to delete the data inside the table, and not the table itself? 
Then, use the TRUNCATE TABLE statement: 

TRUNCATE TABLE table_name

_________________________________________________________________________________________________ 
  
ALTER Table Syntax ans statement 

The ALTER TABLE Statement

The ALTER TABLE statement is used to add, delete, or modify columns in an existing table. 

SQL ALTER TABLE Syntax

To add a column in a table, use the following syntax: 

ALTER TABLE table_name
ADD column_name datatype

To delete a column in a table, use the following syntax (notice that some database systems don’t allow deleting a column): 

ALTER TABLE table_name
DROP COLUMN column_name

To change the data type of a column in a table, use the following syntax: 

ALTER TABLE table_name
ALTER COLUMN column_name datatype

SQL ALTER TABLE Example

Look at the “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

Now we want to add a column named “DateOfBirth” in the “Persons” table. 
We use the following SQL statement: 

ALTER TABLE Persons
ADD DateOfBirth date

Notice that the new column, “DateOfBirth”, is of type date and is going to hold a date. The data type specifies what type of data the column can hold. For a complete reference of all the data types available in MS Access, MySQL, and SQL Server, go to our complete Data Types reference
The “Persons” table will now like this: 

P_Id LastName FirstName Address City DateOfBirth
1 Hansen Ola Timoteivn 10 Sandnes  
2 Svendson Tove Borgvn 23 Sandnes  
3 Pettersen Kari Storgt 20 Stavanger  

Change Data Type Example

Now we want to change the data type of the column named “DateOfBirth” in the “Persons” table. 
We use the following SQL statement: 

ALTER TABLE Persons
ALTER COLUMN DateOfBirth year

Notice that the “DateOfBirth” column is now of type year and is going to hold a year in a two-digit or four-digit format. 


DROP COLUMN Example

Next, we want to delete the column named “DateOfBirth” in the “Persons” table. 
We use the following SQL statement: 

ALTER TABLE Persons
DROP COLUMN DateOfBirth

The “Persons” table will now like this: 

P_Id LastName FirstName Address City
1 Hansen Ola Timoteivn 10 Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari Storgt 20 Stavanger

  
________________________________________________________________________________________________________ 
  
AUTO INCRIMENT IN A FIELD 
Auto-increment allows a unique number to be generated when a new record is inserted into a table. 


 
Very often we would like the value of the primary key field to be created automatically every time a new record is inserted. 
We would like to create an auto-increment field in a table. 

SQL Server 
The following SQL statement defines the “P_Id” column to be an auto-increment primary key field in the “Persons” table: 

CREATE TABLE Persons
(
P_Id int PRIMARY KEY IDENTITY,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)

The MS SQL Server uses the IDENTITY keyword to perform an auto-increment feature. 
By default, the starting value for IDENTITY is 1, and it will increment by 1 for each new record. 
To specify that the “P_Id” column should start at value 10 and increment by 5, change the identity to IDENTITY(10,5). 
To insert a new record into the “Persons” table, we will not have to specify a value for the “P_Id” column (a unique value will be added automatically): 

INSERT INTO Persons (FirstName,LastName)
VALUES (‘Lars’,’Monsen’)

The SQL statement above would insert a new record into the “Persons” table. The “P_Id” column would be assigned a unique value. The “FirstName” column would be set to “Lars” and the “LastName” column would be set to “Monsen”. 
A view is a virtual table. 
This chapter shows how to create, update, and delete a view. 


SQL CREATE VIEW Statement

In SQL, a view is a virtual table based on the result-set of an SQL statement. 
A view contains rows and columns, just like a real table. The fields in a view are fields from one or more real tables in the database. 
You can add SQL functions, WHERE, and JOIN statements to a view and present the data as if the data were coming from one single table. 

SQL CREATE VIEW Syntax

CREATE VIEW view_name AS
SELECT column_name(s)
FROM table_name
WHERE condition

Note: A view always shows up-to-date data! The database engine recreates the data, using the view’s SQL statement, every time a user queries a view. 


SQL CREATE VIEW Examples

If you have the Northwind database you can see that it has several views installed by default. 
The view “Current Product List” lists all active products (products that are not discontinued) from the “Products” table. The view is created with the following SQL: 

CREATE VIEW [Current Product List] AS
SELECT ProductID,ProductName
FROM Products
WHERE Discontinued=No

We can query the view above as follows: 

SELECT * FROM [Current Product List]

Another view in the Northwind sample database selects every product in the “Products” table with a unit price higher than the average unit price: 

CREATE VIEW [Products Above Average Price] AS
SELECT ProductName,UnitPrice
FROM Products
WHERE UnitPrice>(SELECT AVG(UnitPrice) FROM Products)

We can query the view above as follows: 

SELECT * FROM [Products Above Average Price]

Another view in the Northwind database calculates the total sale for each category in 1997. Note that this view selects its data from another view called “Product Sales for 1997”: 

CREATE VIEW [Category Sales For 1997] AS
SELECT DISTINCT CategoryName,Sum(ProductSales) AS CategorySales
FROM [Product Sales for 1997]
GROUP BY CategoryName

We can query the view above as follows: 

SELECT * FROM [Category Sales For 1997]

We can also add a condition to the query. Now we want to see the total sale only for the category “Beverages”: 

SELECT * FROM [Category Sales For 1997]
WHERE CategoryName=’Beverages’

 


SQL Updating a View

You can update a view by using the following syntax: 

SQL CREATE OR REPLACE VIEW Syntax

CREATE OR REPLACE VIEW view_name AS
SELECT column_name(s)
FROM table_name
WHERE condition

Now we want to add the “Category” column to the “Current Product List” view. We will update the view with the following SQL: 

CREATE VIEW [Current Product List] AS
SELECT ProductID,ProductName,Category
FROM Products
WHERE Discontinued=No

 


SQL Dropping a View

You can delete a view with the DROP VIEW command. 

SQL DROP VIEW Syntax

DROP VIEW view_name 
_______________________________________________________________________________________________________ 
  

SQL Server Date Functions

The following table lists the most important built-in date functions in SQL Server: 

Function Description
GETDATE() Returns the current date and time
DATEPART() Returns a single part of a date/time
DATEADD() Adds or subtracts a specified time interval from a date
DATEDIFF() Returns the time between two dates
CONVERT() Displays date/time data in different formats

SQL Date Data Types

MySQL comes with the following data types for storing a date or a date/time value in the database: 

  • DATE – format YYYY-MM-DD
  • DATETIME – format: YYYY-MM-DD HH:MM:SS
  • TIMESTAMP – format: YYYY-MM-DD HH:MM:SS
  • YEAR – format YYYY or YY

SQL Server comes with the following data types for storing a date or a date/time value in the database: 

  • DATE – format YYYY-MM-DD
  • DATETIME – format: YYYY-MM-DD HH:MM:SS
  • SMALLDATETIME – format: YYYY-MM-DD HH:MM:SS
  • TIMESTAMP – format: a unique number

___________________________________________________________________________________________________ 
  
“NULLS” 
   
NULL values represent missing unknown data. 
By default, a table column can hold NULL values. 
This chapter will explain the IS NULL and IS NOT NULL operators. 


SQL NULL Values

If a column in a table is optional, we can insert a new record or update an existing record without adding a value to this column. This means that the field will be saved with a NULL value. 
NULL values are treated differently from other values. 
NULL is used as a placeholder for unknown or inapplicable values. 
Note Note: It is not possible to compare NULL and 0; they are not equivalent. 


SQL Working with NULL Values

Look at the following “Persons” table: 

P_Id LastName FirstName Address City
1 Hansen Ola   Sandnes
2 Svendson Tove Borgvn 23 Sandnes
3 Pettersen Kari   Stavanger

Suppose that the “Address” column in the “Persons” table is optional. This means that if we insert a record with no value for the “Address” column, the “Address” column will be saved with a NULL value. 
How can we test for NULL values? 
It is not possible to test for NULL values with comparison operators, such as =, <, or <>. 
We will have to use the IS NULL and IS NOT NULL operators instead. 


SQL IS NULL

How do we select only the records with NULL values in the “Address” column? 
We will have to use the IS NULL operator: 

SELECT LastName,FirstName,Address FROM Persons
WHERE Address IS NULL

The result-set will look like this: 

LastName FirstName Address
Hansen Ola  
Pettersen Kari  

Note Tip: Always use IS NULL to look for NULL values. 


SQL IS NOT NULL

How do we select only the records with no NULL values in the “Address” column? 
We will have to use the IS NOT NULL operator: 

SELECT LastName,FirstName,Address FROM Persons
WHERE Address IS NOT NULL

The result-set will look like this: 

LastName FirstName Address
Svendson Tove Borgvn 23

______________________________________________________________________________________________________ 

  
  
“DATATYPES” 
   

SQL Server Data Types

Character strings: 

Data type Description Storage
char(n) Fixed-length character string. Maximum 8,000 characters n
varchar(n) Variable-length character string. Maximum 8,000 characters  
varchar(max) Variable-length character string. Maximum 1,073,741,824 characters  
text Variable-length character string. Maximum 2GB of text data  

Unicode strings: 

Data type Description Storage
nchar(n) Fixed-length Unicode data. Maximum 4,000 characters  
nvarchar(n) Variable-length Unicode data. Maximum 4,000 characters  
nvarchar(max) Variable-length Unicode data. Maximum 536,870,912 characters  
ntext Variable-length Unicode data. Maximum 2GB of text data  

Binary types: 

Data type Description Storage
bit Allows 0, 1, or NULL  
binary(n) Fixed-length binary data. Maximum 8,000 bytes  
varbinary(n) Variable-length binary data. Maximum 8,000 bytes  
varbinary(max) Variable-length binary data. Maximum 2GB  
image Variable-length binary data. Maximum 2GB  

Number types: 

Data type Description Storage
tinyint Allows whole numbers from 0 to 255 1 byte
smallint Allows whole numbers between -32,768 and 32,767 2 bytes
int Allows whole numbers between -2,147,483,648 and 2,147,483,647 4 bytes
bigint Allows whole numbers between -9,223,372,036,854,775,808 and 9,223,372,036,854,775,807 8 bytes
decimal(p,s) Fixed precision and scale numbers.
Allows numbers from -10^38 +1 to 10^38 –1. 
The p parameter indicates the maximum total number of digits that can be stored (both to the left and to the right of the decimal point). p must be a value from 1 to 38. Default is 18. 
The s parameter indicates the maximum number of digits stored to the right of the decimal point. s must be a value from 0 to p. Default value is 0 
5-17 bytes
numeric(p,s) Fixed precision and scale numbers.
Allows numbers from -10^38 +1 to 10^38 –1. 
The p parameter indicates the maximum total number of digits that can be stored (both to the left and to the right of the decimal point). p must be a value from 1 to 38. Default is 18. 
The s parameter indicates the maximum number of digits stored to the right of the decimal point. s must be a value from 0 to p. Default value is 0 
5-17 bytes
smallmoney Monetary data from -214,748.3648 to 214,748.3647 4 bytes
money Monetary data from -922,337,203,685,477.5808 to 922,337,203,685,477.5807 8 bytes
float(n) Floating precision number data from -1.79E + 308 to 1.79E + 308.
The n parameter indicates whether the field should hold 4 or 8 bytes. float(24) holds a 4-byte field and float(53) holds an 8-byte field. Default value of n is 53. 
4 or 8 bytes
real Floating precision number data from -3.40E + 38 to 3.40E + 38 4 bytes

Date types: 

Data type Description Storage
datetime From January 1, 1753 to December 31, 9999 with an accuracy of 3.33 milliseconds 8 bytes
datetime2 From January 1, 0001 to December 31, 9999 with an accuracy of 100 nanoseconds 6-8 bytes
smalldatetime From January 1, 1900 to June 6, 2079 with an accuracy of 1 minute 4 bytes
date Store a date only. From January 1, 0001 to December 31, 9999 3 bytes
time Store a time only to an accuracy of 100 nanoseconds 3-5 bytes
datetimeoffset The same as datetime2 with the addition of a time zone offset 8-10 bytes
timestamp Stores a unique number that gets updated every time a row gets created or modified. The timestamp value is based upon an internal clock and does not correspond to real time. Each table may have only one timestamp variable  

Other data types: 

Data type Description
sql_variant Stores up to 8,000 bytes of data of various data types, except text, ntext, and timestamp
uniqueidentifier Stores a globally unique identifier (GUID)
xml Stores XML formatted data. Maximum 2GB
cursor Stores a reference to a cursor used for database operations
table Stores a result-set for later processing

________________________________________________________________________________________ 
  
“FUNCTIONS” 
   
SQL has many built-in functions for performing calculations on data. 


SQL Aggregate Functions

SQL aggregate functions return a single value, calculated from values in a column. 
Useful aggregate functions: 

  • AVG() – Returns the average value
  • COUNT() – Returns the number of rows
  • FIRST() – Returns the first value
  • LAST() – Returns the last value
  • MAX() – Returns the largest value
  • MIN() – Returns the smallest value
  • SUM() – Returns the sum

SQL Scalar functions

SQL scalar functions return a single value, based on the input value. 
Useful scalar functions: 

  • UCASE() – Converts a field to upper case
  • LCASE() – Converts a field to lower case
  • MID() – Extract characters from a text field
  • LEN() – Returns the length of a text field
  • ROUND() – Rounds a numeric field to the number of decimals specified
  • NOW() – Returns the current system date and time
  • FORMAT() – Formats how a field is to be displayed

Tip: The aggregate functions and the scalar functions will be explained in details in the next chapters. 
_________________________________________________________________________________________ 
   
“AVG” function 

The AVG() Function

The AVG() function returns the average value of a numeric column. 

SQL AVG() Syntax

SELECT AVG(column_name) FROM table_name

 


SQL AVG() Example

We have the following “Orders” table: 

O_Id OrderDate OrderPrice Customer
1 2008/11/12 1000 Hansen
2 2008/10/23 1600 Nilsen
3 2008/09/02 700 Hansen
4 2008/09/03 300 Hansen
5 2008/08/30 2000 Jensen
6 2008/10/04 100 Nilsen

Now we want to find the average value of the “OrderPrice” fields. 
We use the following SQL statement: 

SELECT AVG(OrderPrice) AS OrderAverage FROM Orders

The result-set will look like this: 

OrderAverage
950

Now we want to find the customers that have an OrderPrice value higher than the average OrderPrice value. 
We use the following SQL statement: 

SELECT Customer FROM Orders
WHERE OrderPrice>(SELECT AVG(OrderPrice) FROM Orders)

The result-set will look like this: 

Customer
Hansen
Nilsen
Jensen

________________________________________________________________________________________ 
  
“COUNT” function 
   
The COUNT() function returns the number of rows that matches a specified criteria. 


SQL COUNT(column_name) Syntax

The COUNT(column_name) function returns the number of values (NULL values will not be counted) of the specified column: 

SELECT COUNT(column_name) FROM table_name

SQL COUNT(*) Syntax

The COUNT(*) function returns the number of records in a table: 

SELECT COUNT(*) FROM table_name

SQL COUNT(DISTINCT column_name) Syntax

The COUNT(DISTINCT column_name) function returns the number of distinct values of the specified column: 

SELECT COUNT(DISTINCT column_name) FROM table_name

Note: COUNT(DISTINCT) works with ORACLE and Microsoft SQL Server, but not with Microsoft Access. 


SQL COUNT(column_name) Example

We have the following “Orders” table: 

O_Id OrderDate OrderPrice Customer
1 2008/11/12 1000 Hansen
2 2008/10/23 1600 Nilsen
3 2008/09/02 700 Hansen
4 2008/09/03 300 Hansen
5 2008/08/30 2000 Jensen
6 2008/10/04 100 Nilsen

Now we want to count the number of orders from “Customer Nilsen”. 
We use the following SQL statement: 

SELECT COUNT(Customer) AS CustomerNilsen FROM Orders
WHERE Customer=’Nilsen’

The result of the SQL statement above will be 2, because the customer Nilsen has made 2 orders in total: 

CustomerNilsen
2

 


SQL COUNT(*) Example

If we omit the WHERE clause, like this: 

SELECT COUNT(*) AS NumberOfOrders FROM Orders

The result-set will look like this: 

NumberOfOrders
6

which is the total number of rows in the table. 


SQL COUNT(DISTINCT column_name) Example

Now we want to count the number of unique customers in the “Orders” table. 
We use the following SQL statement: 

SELECT COUNT(DISTINCT Customer) AS NumberOfCustomers FROM Orders

The result-set will look like this: 

NumberOfCustomers
3

which is the number of unique customers (Hansen, Nilsen, and Jensen) in the “Orders” table. 
_________________________________________________________________________________________ 
  
“MAX” Function 
   

The MAX() Function

The MAX() function returns the largest value of the selected column. 

SQL MAX() Syntax

SELECT MAX(column_name) FROM table_name

 


SQL MAX() Example

We have the following “Orders” table: 

O_Id OrderDate OrderPrice Customer
1 2008/11/12 1000 Hansen
2 2008/10/23 1600 Nilsen
3 2008/09/02 700 Hansen
4 2008/09/03 300 Hansen
5 2008/08/30 2000 Jensen
6 2008/10/04 100 Nilsen

Now we want to find the largest value of the “OrderPrice” column. 
We use the following SQL statement: 

SELECT MAX(OrderPrice) AS LargestOrderPrice FROM Orders

The result-set will look like this: 

LargestOrderPrice
2000

_______________________________________________________________________________________ 
   
“MIN” Function 
   

The MIN() Function

The MIN() function returns the smallest value of the selected column. 

SQL MIN() Syntax

SELECT MIN(column_name) FROM table_name

 


SQL MIN() Example

We have the following “Orders” table: 

O_Id OrderDate OrderPrice Customer
1 2008/11/12 1000 Hansen
2 2008/10/23 1600 Nilsen
3 2008/09/02 700 Hansen
4 2008/09/03 300 Hansen
5 2008/08/30 2000 Jensen
6 2008/10/04 100 Nilsen

Now we want to find the smallest value of the “OrderPrice” column. 
We use the following SQL statement: 

SELECT MIN(OrderPrice) AS SmallestOrderPrice FROM Orders

The result-set will look like this: 

SmallestOrderPrice
100

______________________________________________________________________________________ 
  
“GROUP” Function 
   
Aggregate functions often need an added GROUP BY statement. 


The GROUP BY Statement

The GROUP BY statement is used in conjunction with the aggregate functions to group the result-set by one or more columns. 

SQL GROUP BY Syntax

SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name

 


SQL GROUP BY Example

We have the following “Orders” table: 

O_Id OrderDate OrderPrice Customer
1 2008/11/12 1000 Hansen
2 2008/10/23 1600 Nilsen
3 2008/09/02 700 Hansen
4 2008/09/03 300 Hansen
5 2008/08/30 2000 Jensen
6 2008/10/04 100 Nilsen

Now we want to find the total sum (total order) of each customer. 
We will have to use the GROUP BY statement to group the customers. 
We use the following SQL statement: 

SELECT Customer,SUM(OrderPrice) FROM Orders
GROUP BY Customer

The result-set will look like this: 

Customer SUM(OrderPrice)
Hansen 2000
Nilsen 1700
Jensen 2000

Nice! Isn’t it? 🙂 
Let’s see what happens if we omit the GROUP BY statement: 

SELECT Customer,SUM(OrderPrice) FROM Orders

The result-set will look like this: 

Customer SUM(OrderPrice)
Hansen 5700
Nilsen 5700
Hansen 5700
Hansen 5700
Jensen 5700
Nilsen 5700

The result-set above is not what we wanted. 
Explanation of why the above SELECT statement cannot be used: The SELECT statement above has two columns specified (Customer and SUM(OrderPrice). The “SUM(OrderPrice)” returns a single value (that is the total sum of the “OrderPrice” column), while “Customer” returns 6 values (one value for each row in the “Orders” table). This will therefore not give us the correct result. However, you have seen that the GROUP BY statement solves this problem. 


GROUP BY More Than One Column

We can also use the GROUP BY statement on more than one column, like this: 

SELECT Customer,OrderDate,SUM(OrderPrice) FROM Orders
GROUP BY Customer,OrderDate 
_______________________________________________________________________________________________ 
  
“HAVING” Clause 
   

The HAVING Clause

The HAVING clause was added to SQL because the WHERE keyword could not be used with aggregate functions. 

SQL HAVING Syntax

SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name
HAVING aggregate_function(column_name) operator value

SQL HAVING Example

We have the following “Orders” table: 

O_Id OrderDate OrderPrice Customer
1 2008/11/12 1000 Hansen
2 2008/10/23 1600 Nilsen
3 2008/09/02 700 Hansen
4 2008/09/03 300 Hansen
5 2008/08/30 2000 Jensen
6 2008/10/04 100 Nilsen

Now we want to find if any of the customers have a total order of less than 2000. 
We use the following SQL statement: 

SELECT Customer,SUM(OrderPrice) FROM Orders
GROUP BY Customer
HAVING SUM(OrderPrice)<2000

The result-set will look like this: 

Customer SUM(OrderPrice)
Nilsen 1700

Now we want to find if the customers “Hansen” or “Jensen” have a total order of more than 1500. 
We add an ordinary WHERE clause to the SQL statement: 

SELECT Customer,SUM(OrderPrice) FROM Orders
WHERE Customer=’Hansen’ OR Customer=’Jensen’
GROUP BY Customer
HAVING SUM(OrderPrice)>1500

The result-set will look like this: 

Customer SUM(OrderPrice)
Hansen 2000
Jensen 2000

___________________________________________________________________________________________________ 
  
  

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